Last modified: November 26, 2024

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PostgreSQL

• PostgreSQL: a powerful, open-source object-relational database management system (ORDBMS)
• Developed and maintained by the PostgreSQL Global Development Group
• Suitable for a wide range of applications, from small-scale projects to enterprise-level systems

Features

ACID Compliance

Supports ACID transactions, ensuring data consistency and reliability

Extensibility

• Allows custom functions, operators, data types, and index methods
• Supports stored procedures, triggers, and views

Concurrency Control

Uses Multi-Version Concurrency Control (MVCC) to handle concurrent access without locking

Robust Security

Offers strong encryption, authentication, and authorization mechanisms

Cross-Platform

Compatible with various operating systems, including Windows, macOS, Linux, and Unix

Full-Text Search

Built-in support for text search and advanced indexing

Spatial Data Support

Support for geographic objects and spatial queries through PostGIS extension

High Availability and Replication

Supports various replication methods, including streaming replication and logical replication

PostgreSQL Commands

Creating a Database

CREATE DATABASE database_name;

Creating Tables

CREATE TABLE table_name (
column_name1 datatype PRIMARY KEY,
column_name2 datatype NOT NULL,
...
);

Inserting Data

INSERT INTO table_name (column1, column2, ...)
VALUES (value1, value2, ...);

Querying Data

SELECT column1, column2, ...
FROM table_name
WHERE condition;

Updating Data

UPDATE table_name
SET column1 = value1, column2 = value2, ...
WHERE condition;

Deleting Data

DELETE FROM table_name
WHERE condition;

Dropping Tables

DROP TABLE table_name;

Administration and Management

pgAdmin

A popular, open-source graphical administration tool for PostgreSQL

Command-Line Client

A text-based interface for executing SQL queries and managing databases (e.g., psql)

Performance Tuning

PostgreSQL provides various configuration options for optimizing performance

Backup and Recovery

Supports logical and physical backups using tools like pg_dump and pg_basebackup

Monitoring

Built-in statistics collector for monitoring and diagnosing performance issues

Use Cases

• Common choice for web applications due to its flexibility and extensibility
• Widely used in GIS applications due to PostGIS support
• Suitable for data warehousing and analytical processing workloads
• Ideal for large-scale enterprise applications requiring a robust and feature-rich RDBMS

ENgine

PostgreSQL uses a single, unified storage engine. However, PostgreSQL provides a rich and flexible architecture for handling data and offers many advanced features. Unlike MySQL, which uses multiple storage engines, PostgreSQL uses a unified engine but provides mechanisms to customize storage and indexing behaviors.

Key Features of PostgreSQL’s Storage System

1. Unified Storage Engine

• PostgreSQL uses a single, robust storage engine for all operations, ensuring ACID compliance and high performance across a variety of workloads.

2. Table Storage Models

• PostgreSQL organizes data in tables using a row-based storage model.
• Heap Storage:
  • Default storage model for tables.
  • Data is stored in no particular order, and MVCC (Multiversion Concurrency Control) ensures consistency without locking reads.

3. MVCC (Multiversion Concurrency Control)

• PostgreSQL uses MVCC to handle transactions and concurrency.
• Instead of locking rows, it creates multiple versions of rows to ensure consistency.
• MVCC supports advanced features like:
  • Point-in-time recovery (PITR).
  • Non-blocking reads during write operations.

4. Tablespaces

• PostgreSQL supports tablespaces, allowing users to control where data files are stored on disk.
• Useful for optimizing storage performance and managing large-scale data systems.

5. TOAST (The Oversized-Attribute Storage Technique)

• PostgreSQL can handle large data fields like blobs, JSON, or XML efficiently using TOAST.
• Automatically stores large column data externally and references it in the main table.

Indexing Options in PostgreSQL

PostgreSQL supports a variety of indexing methods, allowing customization for different workloads:

1. B-Tree:
2. Default index type, ideal for most general-purpose queries.
3. Hash:
4. Optimized for equality lookups (e.g., = or IN).
5. GIN (Generalized Inverted Index):
6. Efficient for full-text searches and indexing JSON/array fields.
7. GiST (Generalized Search Tree):
8. Useful for spatial data, geometric searches, and full-text indexing.
9. BRIN (Block Range Index):
10. Optimized for large, sequentially stored data sets like time-series data.
11. SP-GiST (Space Partitioned GiST):
12. Efficient for non-balanced tree structures like quadtrees or k-d trees.
13. Bloom Filters:
14. Space-efficient, probabilistic data structures for certain query types.

Advanced Features in PostgreSQL

1. Partitioning

• PostgreSQL supports declarative partitioning (range, list, and hash) to optimize large data sets by dividing them into smaller, manageable parts.

2. Foreign Data Wrappers (FDW)

• Allows PostgreSQL to interact with external data sources (e.g., other databases, files) as if they were local tables.

3. Custom Data Types

• PostgreSQL allows users to define their own data types, providing flexibility for domain-specific applications.

4. JSON and JSONB Support

• PostgreSQL has robust support for semi-structured data through JSON and JSONB.
• JSONB (binary JSON) provides efficient indexing and querying capabilities.

5. Full-Text Search

• Built-in full-text search capabilities enable efficient querying of textual data.

6. PL/pgSQL and Other Procedural Languages

• PostgreSQL supports embedded procedural languages (e.g., PL/pgSQL, PL/Python, PL/Perl), allowing complex application logic to run within the database.

Storage Customization in PostgreSQL

• While PostgreSQL doesn’t use multiple storage engines like MySQL, it offers advanced configuration and extension capabilities to tailor the database to specific needs:
• Extensions like pg_partman for partition management.
• TimescaleDB for time-series data.
• PostGIS for geographic and spatial data.

Comparison to MySQL

• Single Unified Engine vs. Multiple Engines:
• PostgreSQL has a unified engine with deep extensibility, while MySQL offers multiple engines (e.g., InnoDB, MyISAM).
• Concurrency: PostgreSQL’s MVCC implementation often outperforms MySQL for high-concurrency scenarios.
• Extensibility: PostgreSQL supports custom data types, extensions, and advanced indexing, making it more flexible for complex applications.
• ACID Compliance: PostgreSQL is fully ACID-compliant by default, whereas MySQL depends on the storage engine (e.g., InnoDB is ACID-compliant, MyISAM is not).